Part 1: T0 versus T90 physiology

Figure 1

Figure 1. True mean (+/- SE) physiology of T0 coral fragments (one per colony; n = 8-14) denoted by black cross with (A) individual colony physiology denoted by coloured shape or (B) native reef environment.

Figure 2

Figure 2. True mean (+/- SE) T0 and T90 coral fragment physiology of (a) S. siderea, (b) P. strigosa, (c) P. astreoides, and (d) U. tenuifolia with individual coral fragment physiology denoted by points. T0 corals are represented by green stars. Blue denotes 28C, red denotes 31C, and shape corresponds to pCO2 treatment conditions of T90 fragments.

Part 2: Effects of treatment on T90 physiology


Figure 3

Figure 3. Modelled 95% confidence interval of (a) S. siderea, (b) P. strigosa, (c) P. astreoides, and (d) U. tenuifolia physiology with individual coral fragment physiology denoted by points. Blue denotes 28C and red denotes 31C, with pCO2 treatment along the x axis.

Part 3: Bleaching over time (using colour intensity)

Table 1. Colour Intensity Linear Models
SSID
PSTR
PAST
UTEN
comparison R2 p.value comparison R2 p.value comparison R2 p.value comparison R2 p.value
chla v sum 0.116 0.0005 chla v sum 0.327 0e+00 chla v sum 0.317 0.0000 chla v sum 0.029 0.1651
chla v red 0.136 0.0002 chla v red 0.436 0e+00 chla v red 0.291 0.0000 chla v red 0.023 0.1909
chla v blue 0.056 0.0130 chla v blue 0.133 5e-04 chla v blue 0.276 0.0000 chla v blue 0.028 0.1681
chla v green 0.122 0.0004 chla v green 0.364 0e+00 chla v green 0.316 0.0000 chla v green 0.031 0.1591
den v sum 0.217 0.0000 den v sum 0.388 0e+00 den v sum -0.015 0.9279 den v sum -0.017 0.5217
den v red 0.234 0.0000 den v red 0.399 0e+00 den v red -0.015 0.9936 den v red -0.026 0.7067
den v blue 0.143 0.0001 den v blue 0.192 0e+00 den v blue -0.015 0.9747 den v blue -0.001 0.3329
den v green 0.218 0.0000 den v green 0.390 0e+00 den v green -0.014 0.8190 den v green -0.016 0.4935


Figure 4

Figure 4. Text goes here

Notes:

  • Red best predicts denisty, but colour overall predicts density better than chlorophyll in SSID
  • Red best predicts chlorophyll, but any channel (with the exception of blue) predicts both density and chlorophyll in PSTRs
  • Colour intensity predicts chlorophyll, but not density in PAST
  • No colour analysis predicts UTEN bleaching


Figure 5

Figure 5. Text goes here



Part 4: Comparison of physiological parameters

Siderastrea siderea

Models were fit by either temperature (blue/red) or pCO2 (pink/green/orange/darkred) depending on best linear model fit

Working analyses

Preliminary statistics (basic linear model and anova)

SSID linear models p-values
Carbohydrate Protein Symbiont Density Chlorophyll a Colour Intensity
Temperature 0.0022 0.7612 0.1781 0.0063 0.0405
280 pCO2 0.6774 0.7228 0.7211 0.5132 0.2808
700 pCO2 0.2133 0.3481 0.1362 0.0067 0.2041
2800 pCO2 0.8782 0.2430 0.0001 0.0000 0.0004
Reef Environment 0.6175 0.2905 0.2580 0.1641 0.0011
Temperature x Reef NA 0.0660 0.0540 NA NA
PSTR linear models p-values
Carbohydrate Protein Symbiont Density Chlorophyll a Colour Intensity
Temperature 0.0006 0.0001 0.0005 0.0002 0.0000
280 pCO2 0.4235 0.1194 0.8763 0.0645 0.6704
700 pCO2 0.3631 0.7584 0.1746 0.1886 0.2143
2800 pCO2 0.6688 0.9277 0.0973 0.1155 0.3556
Reef Environment 0.1361 0.5369 0.0001 0.0053 0.0387
Temperature x Reef NA NA 0.0424 NA 0.0367
PAST linear models p-values
Carbohydrate Protein Symbiont Density Chlorophyll a Colour Intensity
Temperature 0.0492 0.0739 0.4838 0.0359 0.0004
280 pCO2 0.6023 0.4606 0.5614 0.6830 0.0523
700 pCO2 0.0196 0.1696 0.2129 0.0058 0.0046
2800 pCO2 0.0121 0.0099 0.5500 0.0008 0.1385
Reef Environment 0.1508 0.2345 0.5783 0.8997 0.4500
Temperature x 280 pCO2 NA NA NA 1.1949138702567e-09 NA
Temperature x 700 pCO2 NA NA NA 2.13430417166503e-05 NA
Temperature x 2800 pCO2 NA NA NA 0.231211071936069 NA
UTEN linear models p-values
Carbohydrate Protein Symbiont Density Chlorophyll a Colour Intensity
Temperature 0.3819 0.5284 0.3287 0.0058 0.0000
280 pCO2 0.2115 0.4150 0.6347 0.4250 0.8840
700 pCO2 0.6568 0.5509 0.3582 0.2885 0.0150
2800 pCO2 0.8366 0.7393 0.3587 0.7004 0.0535
Reef Environment 0.6180 0.9055 0.3112 0.4654 0.0586

T90 plot of all parameters by reefzone

PCA of physiology at T90

Comparison between physiological parameters per fragment Linear Regression between carbohydrate and protein

## 
## Call:
## lm(formula = pro ~ carb, data = df.90b)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.68459 -0.12391 -0.04553  0.09898  0.60632 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  0.10883    0.01890   5.757 2.01e-08 ***
## carb         0.28467    0.02132  13.350  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.187 on 320 degrees of freedom
##   (1 observation deleted due to missingness)
## Multiple R-squared:  0.3577, Adjusted R-squared:  0.3557 
## F-statistic: 178.2 on 1 and 320 DF,  p-value: < 2.2e-16
Linear Regression between chlorophyll and symbiont density

## 
## Call:
## lm(formula = chla ~ den, data = df.90b)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -134.15  -43.09  -20.60   26.54  479.49 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   59.291      5.221  11.357  < 2e-16 ***
## den            5.959      1.361   4.378 1.63e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 69.35 on 319 degrees of freedom
##   (2 observations deleted due to missingness)
## Multiple R-squared:  0.05667,    Adjusted R-squared:  0.05371 
## F-statistic: 19.16 on 1 and 319 DF,  p-value: 1.628e-05
Linear Regression between colour intensity and symbiont density

## 
## Call:
## lm(formula = sum_bw5 ~ den, data = df.90b)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -360.06  -77.49   28.33  105.07  185.65 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) -239.8862    10.3759 -23.120   <2e-16 ***
## den            0.2194     2.5581   0.086    0.932    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 128.7 on 276 degrees of freedom
##   (45 observations deleted due to missingness)
## Multiple R-squared:  2.666e-05,  Adjusted R-squared:  -0.003596 
## F-statistic: 0.007358 on 1 and 276 DF,  p-value: 0.9317
Linear Regression between colour intensity and chlorophyll

## 
## Call:
## lm(formula = sum_bw5 ~ chla, data = df.90b)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -314.37  -70.34   24.01  100.32  189.37 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept) -291.27978   10.31268 -28.245  < 2e-16 ***
## chla           0.66159    0.09593   6.897 3.58e-11 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 118.9 on 278 degrees of freedom
##   (43 observations deleted due to missingness)
## Multiple R-squared:  0.1461, Adjusted R-squared:  0.143 
## F-statistic: 47.57 on 1 and 278 DF,  p-value: 3.581e-11
Linear Regression between protein and chlorophyll

## 
## Call:
## lm(formula = pro ~ chla, data = df.90b)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.84382 -0.15670 -0.01467  0.13149  0.66354 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 0.1955664  0.0161970   12.07   <2e-16 ***
## chla        0.0016608  0.0001573   10.56   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.2007 on 321 degrees of freedom
## Multiple R-squared:  0.2578, Adjusted R-squared:  0.2555 
## F-statistic: 111.5 on 1 and 321 DF,  p-value: < 2.2e-16
Linear Regression between carbohydrate and chlorophyll

## 
## Call:
## lm(formula = carb ~ chla, data = df.90b)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -0.9398 -0.3286 -0.1149  0.2597  2.2662 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 0.5493115  0.0367617  14.943  < 2e-16 ***
## chla        0.0025514  0.0003567   7.152 5.84e-12 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.4552 on 320 degrees of freedom
##   (1 observation deleted due to missingness)
## Multiple R-squared:  0.1378, Adjusted R-squared:  0.1351 
## F-statistic: 51.16 on 1 and 320 DF,  p-value: 5.839e-12
Linear Regression between protein and calcification rate

## 
## Call:
## lm(formula = pro ~ rate, data = df.90b)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.61621 -0.14542 -0.04558  0.11987  0.68780 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  0.24088    0.01288   18.70   <2e-16 ***
## rate         0.17596    0.01402   12.55   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.1939 on 278 degrees of freedom
##   (43 observations deleted due to missingness)
## Multiple R-squared:  0.3618, Adjusted R-squared:  0.3595 
## F-statistic: 157.6 on 1 and 278 DF,  p-value: < 2.2e-16
Linear Regression between carbohydrate and calcification rate

## 
## Call:
## lm(formula = carb ~ rate, data = df.90b)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -1.07630 -0.28281 -0.05503  0.16522  2.08199 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  0.59443    0.02932  20.273  < 2e-16 ***
## rate         0.23129    0.03190   7.251 4.15e-12 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.441 on 277 degrees of freedom
##   (44 observations deleted due to missingness)
## Multiple R-squared:  0.1595, Adjusted R-squared:  0.1565 
## F-statistic: 52.58 on 1 and 277 DF,  p-value: 4.145e-12
Linear Regression between chlorophyll and calcification rate

## 
## Call:
## lm(formula = chla ~ rate, data = df.90b)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -157.09  -37.94  -11.42   23.36  417.72 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   58.027      4.112   14.11   <2e-16 ***
## rate          49.589      4.476   11.08   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 61.91 on 278 degrees of freedom
##   (43 observations deleted due to missingness)
## Multiple R-squared:  0.3063, Adjusted R-squared:  0.3038 
## F-statistic: 122.8 on 1 and 278 DF,  p-value: < 2.2e-16
Linear Regression between symbiont density and calcification rate

## 
## Call:
## lm(formula = den ~ rate, data = df.90b)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -2.7465 -1.9950 -0.8537  0.6905 19.5315 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   2.6506     0.2023  13.103   <2e-16 ***
## rate          0.1482     0.2196   0.675      0.5    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 3.025 on 276 degrees of freedom
##   (45 observations deleted due to missingness)
## Multiple R-squared:  0.001647,   Adjusted R-squared:  -0.00197 
## F-statistic: 0.4553 on 1 and 276 DF,  p-value: 0.5004